Development Methodology

The required breadth of material property data needed for the development of universal ML system for predicting material properties can be in principle obtained from a large database containing structural material properties, such as Total Materia Horizon [], which comprises more than 500,000 materials. However, there is no single ML model capable of effectively using its 20 million property records for dozens of material properties to deliver predictions of any acceptable quality. Therefore, classifying and grouping materials, normalizing their properties and conditions (a combination of thermic-, mechanical- and other processing patterns of a material), and then applying dataset splitting and division, is essential to enable effective ML on such comprehensive and diversified datasets.